1. Field
The following description relates to a microphone signal compensation apparatus and method thereof, and more particularly, to a microphone signal compensation apparatus and method thereof that compensates for a difference in a characteristic for a microphone array including a plurality of microphones.
2. Description of Related Art
Technologies for microphone array-based speech enhancement and Automatic Speech Recognition (ASR) have been researched to improve Voice User Interface (VUI). A dual microphone array helps reduce directional interference, and may be equipped in pocket-size devices, such as Personal Digital Assistants (PDAs) or mobile phones.
Microphone arrays for enhancing a voice separation function and methods of using microphone arrays in conjunction with speech recognizers are primarily based on a Generalized Sidelobe Canceller (GSC) framework. Various modified examples have been proposed to overcome model errors due to a location of a target speaker, an acoustic response, or microphone characteristics. In particular, when a location of a microphone is uncertain, speech leakage may be reduced by incorporating multiple linear constraints in a design of a fixed spatial pre-processor.
To compensate for a channel mismatch using a self-calibration scheme, various methods have been proposed to develop robust superdirective beamformers based on correlation analysis of signals and to increase statistic values of microphone characteristics.
Although these methods may reduce speech distortion, alternately updating coefficients of an adaptive filter of the self-calibration scheme and Adaptive Noise Cancellation (ANC) in an algorithm based on the GSC framework is a relatively complex process. In addition, a small-sized array may be sensitive to a difference in a characteristic among microphones; accordingly, a greater number of microphones may be used to improve noise reduction performance, thereby incurring high costs. Moreover, calculation may be performed in each of the microphones, increasing calculation loads. In other words, performance of a GSC framework is generally inferior to a simple Delay-and-Sum Beamformer (DSB) in speech recognition.
People are capable of focusing on only a desired sound among mixed sounds. Based on such an auditory system, a variety of noise removal technologies have been developed. Among these technologies, most implement noise removal schemes based on a person's ability to recognize which sound comes from which direction and distinguish a sound coming from a desired direction to listen specifically to the desired sound. In a person's binaural system, a direction from which a sound is received may be determined based on an Interaural Time Difference (ITD), an Interaural Phase Difference (IPD), an Interaural Intensity Difference (IID), and the like. However, a process of determining a sound generation direction in a microphone array system may be degraded due to a difference in a characteristic among microphones or non-ideal acoustic characteristics (for example, reverberation), thereby deteriorating noise reduction performance and blocking a target speech.